Radionuclides emit photon radiation (x-rays and gamma-rays) at distinct, characteristic energies. These monoenergetic emissions travel from the radionuclide source and interact with surrounding materials in ways that can result in partial or full energy deposition in the material. Instrumentation for the measurement of photon radiation includes a sensor or detector. Photons can deposit either full energy or partial energy (some lost on the way to the detector or some escapes after interacting) in the detector. Radiation detectors convert the radiation energies to equivalent electrical signals. These electrical signals are then processed, filtered, amplified and digitized. Typical spectroscopy systems store each incoming signal pulse as a count in a histogram, where each count is stored in an energy bin or channel that correlates to the amplitude of the corresponding pulse. The resulting spectrum is a pulse height frequency distribution, with a shape related to the energy distribution of the measured radiation. Full energy depositions will tend to be indicated in the spectrum by clumps, or peaks. Partial energy depositions will tend to be more spread out, forming the non-peaked continuum. Since different radionuclides emit radiation with distinct energy distributions, analyzing the spectrum can provide information about what radionuclides make up the source of radiation.
Spectral analysis requires that the specific measurement system characteristics are known and recorded in the form of calibrations so that the spectrum can be properly interpreted. These calibrations include an energy calibration, shape calibration, and efficiency calibration. The energy calibration indicates what range of energies (or pulse heights) is collected in each spectrum channel. The shape calibration indicates the energy resolution of the system at any given energy. Monoenergetic radiation causes a collection of counts at the corresponding energy (at the channel specified by the energy calibration) with a characteristic spread, or shape, with counts spilling into adjacent channels. The energy resolution is a measure of how wide (in channels or energy) a monoenergetic photon source would appear in the spectrum in the form of a more or less Gaussian (Normal) distribution, known as a peak. The efficiency calibration indicates the relation between the number of counts seen in the spectrum at a given energy and the corresponding number of radiation emissions produced at the source at that energy. Typically, this efficiency calibration relates only the counts from photons that have not interacted on the way to the detector from the source, and have not lost any energy other than in the detector (only full energy depositions). This type of efficiency calibration is known as a peak efficiency calibration. Efficiency calibrations are not just a function of the detection system (as is primarily the case with the energy and shape calibrations), but will also vary depending on the source-detector geometry or anything that affects the probability of full energy deposition inside the detector.
Nuclide identification (NID) algorithms determine the identity and quantity of radionuclides based on the output of radiation measurement instrumentation. This output includes the spectrum (histogram indicating the frequency of counts in sequential energy bins or channels) and calibrations that define the spectral channel energy ranges (energy calibration), expected monoenergetic response function (shape calibration) and the count rate to emission rate conversion (efficiency calibration). NID algorithms correlate the spectral information as interpreted by the supplied calibrations with nuclides provided by a reference nuclide library. For each nuclide described in the library, the information provided usually includes expected monoenergetic emission energies with corresponding relative emission rates. The way the NID algorithm correlates all of this information is usually controlled by user-specified parameters. In general, there have been two paradigms used to implement NID algorithms: peak correlation and deconvolution.
Peak correlation uses the energy and shape calibration to locate peaks (find energies) in the spectrum and to determine their areas (corresponding count rates). Identification is done by directly correlating library energies to peak energies found in the spectrum. Sometimes least-squares fitting is used to determine how much peak area ought to be attributed to nuclides with similar energies (interference correction). The geometry dependent efficiency calibration is used to convert peak count rates to expected source emission rates and therefore quantify nuclide activities. Peak correlation is the dominant paradigm in the industry.
Deconvolution (sometimes referred to as spectrum stripping or unfolding) uses a full energy response function to fit expected nuclide energy distributions to the measured spectrum. This requires that either the shape calibration function be expanded beyond only a monoenergetic response or the nuclide library be expanded to include the full energy response for each nuclide (template matching). The full energy response of the measurement system depends on a number of variables, including the nuclide emission energies, operating conditions, source-detector geometry and the counting rate. An advantage of deconvolution is that it uses all of the available information provided by the spectrum (rather than just the peak data). A disadvantage is that it relies on the accuracy of the full energy response function to correctly identify and quantify nuclides and the results may be more sensitive to measurement variables than peak correlation. Deconvolution can also sometimes require extensive measurement system full energy characterization, a more difficult and laborious process than typical peak shape calibration, with a more limited scope of applicability.